TradingAgents/tradingagents/agents/analysts/news_analyst.py

99 lines
4.8 KiB
Python

from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from tradingagents.agents.utils.agent_utils import get_news, get_global_news
from tradingagents.agents.utils.logging_utils import log_report_preview
from tradingagents.agents.utils.tool_runner import (
extract_text_from_content,
run_chain_with_tools,
)
def create_news_analyst(llm):
def news_analyst_node(state):
scheduled_list = state.get("scheduled_analysts", []) or []
scheduled_plan_list = state.get("scheduled_analysts_plan", []) or []
scheduled_plan = {item.lower() for item in scheduled_plan_list}
action = state.get("orchestrator_action", "").lower()
ticker = state.get("target_ticker") or state["company_of_interest"]
if (scheduled_plan and "news" not in scheduled_plan) or action not in ("", "monitor", "escalate", "trade", "execute"):
return {
"news_report": "News analyst skipped by orchestrator directive.",
"scheduled_analysts": [item for item in scheduled_list if item.lower() != "news"],
"scheduled_analysts_plan": scheduled_plan_list,
}
current_date = state["trade_date"]
tools = [
get_news,
get_global_news,
]
system_message = (
"You are a news researcher tasked with analyzing recent news and trends over the past week. Please write a comprehensive report of the current state of the world that is relevant for trading and macroeconomics. Use the available tools: get_news(query, start_date, end_date) for company-specific or targeted news searches, and get_global_news(curr_date, look_back_days, limit) for broader macroeconomic news. Do not simply state the trends are mixed, provide detailed and finegrained analysis and insights that may help traders make decisions."
+ """ Make sure to append a Markdown table at the end of the report to organize key points in the report, organized and easy to read."""
)
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"You are a helpful AI assistant, collaborating with other assistants."
" Use the provided tools to progress towards answering the question."
" If you are unable to fully answer, that's OK; another assistant with different tools"
" will help where you left off. Execute what you can to make progress."
" If you or any other assistant has the FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** or deliverable,"
" prefix your response with FINAL TRANSACTION PROPOSAL: **BUY/HOLD/SELL** so the team knows to stop."
" You have access to the following tools: {tool_names}.\n{system_message}"
"For your reference, the current date is {current_date}. We are looking at the company {ticker}",
),
MessagesPlaceholder(variable_name="messages"),
]
)
prompt = prompt.partial(system_message=system_message)
prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
prompt = prompt.partial(current_date=current_date)
prompt = prompt.partial(ticker=ticker)
chain = prompt | llm.bind_tools(tools)
try:
print(f"[News Analyst] Running analysis for {ticker} | scheduled={scheduled_list}")
except Exception:
pass
try:
result, message_history, tool_runs = run_chain_with_tools(
chain,
tools,
state["messages"],
)
except Exception as exc:
updated_schedule = [item for item in scheduled_list if item.lower() != "news"]
report = f"News analyst failed: {exc}"
return {
"messages": state["messages"],
"news_report": report,
"scheduled_analysts": updated_schedule,
"scheduled_analysts_plan": scheduled_plan_list,
}
report = extract_text_from_content(getattr(result, "content", "")) or "News analyst produced no narrative."
updated_schedule = [item for item in scheduled_list if item.lower() != "news"]
payload = {
"messages": message_history,
"news_report": report,
"scheduled_analysts": updated_schedule,
"scheduled_analysts_plan": scheduled_plan_list,
}
log_report_preview("News Analyst", ticker, report)
try:
print(
f"[News Analyst] Completed step for {ticker} | tool_runs={tool_runs} | report_len={len(report) if report else 0}"
)
except Exception:
pass
return payload
return news_analyst_node